Abstract
Due to the massive popularity of digital images and videos over the past several decades, the need for automated quality assessment (QA) is greater than ever. Accordingly, the impetus on QA research has focused on improving prediction accuracy. However, for many application areas, such as consumer electronics, the runtime performance and related computational considerations are equally as important as the accuracy. Most modern QA algorithms exhibit a large computational complexity. However, the large complexity of these algorithms does not necessarily prohibit their ability of achieving low runtimes if hardware resources are used appropriately. GPUs, which offer a large amount of parallelism and a specialized memory hierarchy, should be well-suited for QA algorithm deployment.
Original language | English (US) |
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Pages (from-to) | 36-41 |
Number of pages | 6 |
Journal | IS and T International Symposium on Electronic Imaging Science and Technology |
DOIs | |
State | Published - 2017 |
Event | Image Quality and System Performance XIV, IQSP 2017 - Burlingame, United States Duration: Jan 29 2017 → Feb 2 2017 |
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics